Delivering the Ultimate Customer Experience with Data + Culture
Data leaders are also consumers, and like me you’ve probably been asked many times to provide feedback to a company you’ve chosen for a product or service. What happens then? How do companies actually use data to improve the customer experience? In most cases you probably don’t see a change in that company, which means that giving feedback feels like a waste of time.
As I’ve noted elsewhere, even the most well-meaning product managers and customer service reps don’t stand a chance in companies that have made only superficial investments in customer experience (CX). This starts with the way they determine priorities, purchase technology, and build a data culture.
In the example I’ve provided, you’ll find that most companies know their why (improve CX), know their what (collect feedback), but don’t follow through on their how. In other words, how will these CX efforts have an impact on their organization? Many times, success or failure is a matter of culture, and it’s where the gap comes in.
Lost in technology
Technology is certainly an essential part of an innovative, customer-focused company, but technology alone will not get you there. There are so many tools out there helping us to solve so many problems that people lose focus on the things that matter and that are really important for an organization. Like data culture.
If you get an inside look at as many large enterprises as I do, you’ll see a surprising and consistent thing. On average, only one-third of applications are interconnected. Everybody wants to be a data-driven organization and to move towards that, but they can’t get there with disconnected systems. Organizations have a lot of data these days because they’ve been collecting data for a long time. But unless they can surface that data and make it available to people who can take action on it, nothing is going to change.
Think of it this way: with every new application you build, you are building tomorrow’s legacy software. I see too many products that were brought in as temporary fixes for six months, and 15 years later they are still there. When you think of an application, project, or process that you are trying to bring in, make sure that
- It’s solving problems
- It’s innovative
- It will be easy to replace
- It will be dynamic so it can grow with time
In fact, before you even consider purchasing a new solution to solve a problem, focus your attention on what you already have and how you can optimize it. Anything else you’re bringing in should logically build on your existing technology infrastructure and processes, because they all need to be aligned. A bit like Patagonia, I encourage data leaders to look into their organizations and determine whether there is a real need to buy another tool, or whether they can continue to get more wear out of what they already have.
The one-two data culture combination
In addition to the right technology, data leaders need to focus on creating a data-driven culture. That means robust data strategy and leveraging everything they have to deliver customer excellence. There should be cross-functional teams in place that can act on the strategy and make this change available, as well as a center for enablement that focuses on creating the right strategies, assets, processes and knowledge.
Pioneers I see in industries like the healthcare industry or finance are all alike in this way. They bring new and better products to market and are a step ahead of their competitors. That’s because they have created cultures where innovation is supported and where they have the ability to leverage data analytics and an insights-driven approach to solve customer problems and improve the user experience. They operate from a place of clarity about this.
This cultural change should come from the top, yet what I too often see is this: there is a change in leadership in a company, but the change new leaders choose to make is in their data products. No one is really looking back and thinking, Does this even make sense for us at this point? That’s why a lot of companies have a soup of various technologies. They may have two or three gateways when one would suffice. They may have two or three data analytics products as well as a couple of different middleware products that don’t talk to each other. This is how you end up with disconnected organizations where you have all the tools, people who have learned all of these tools, but they’re all isolated from each other. And that leads to frustration.
To use any product well, we have to be culturally specific in how that tool is implemented. One cannot live without the other. In the end, we are all in the business of improving people’s lives. And to do that, we must focus on our organizational culture.
5 strategies for CX success
If you are a data leader coming into an organization with low customer experience scores, keep these priorities in mind:
- Don’t divorce the people issues from the technology issues and the change management issues.
- Look into your application ecosystem and start to prioritize what is really working and what you can shelve or even get rid of.
- Organize around a few clear achievable goals and not try to do everything at once.
- Keep your ear to the tracks and listen to what customers are sort of asking for, even if they don’t quite articulate it that clearly.
- Based on this input, look for opportunities where there is an open space in the market for a product enhancement or an entirely new product.
Think of data as the lifeblood of your organization and good data strategy and technology as its beating heart. But to improve your customers’ experiences and move your organization forward effectively, now and in the future, you must have a data-driven culture that everyone values.